WO2010016271A1 - スペクトル平滑化装置、符号化装置、復号装置、通信端末装置、基地局装置及びスペクトル平滑化方法 - Google Patents

スペクトル平滑化装置、符号化装置、復号装置、通信端末装置、基地局装置及びスペクトル平滑化方法 Download PDF

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WO2010016271A1
WO2010016271A1 PCT/JP2009/003799 JP2009003799W WO2010016271A1 WO 2010016271 A1 WO2010016271 A1 WO 2010016271A1 JP 2009003799 W JP2009003799 W JP 2009003799W WO 2010016271 A1 WO2010016271 A1 WO 2010016271A1
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Prior art keywords
spectrum
subband
unit
representative value
smoothing
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PCT/JP2009/003799
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English (en)
French (fr)
Japanese (ja)
Inventor
智史 山梨
押切　正浩
利幸 森井
江原　宏幸
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パナソニック株式会社
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Priority to US13/057,454 priority Critical patent/US8731909B2/en
Priority to JP2010523772A priority patent/JP5419876B2/ja
Priority to RU2011104350/08A priority patent/RU2510536C9/ru
Priority to DK09804758.2T priority patent/DK2320416T3/da
Priority to CN2009801283823A priority patent/CN102099855B/zh
Priority to MX2011001253A priority patent/MX2011001253A/es
Priority to ES09804758.2T priority patent/ES2452300T3/es
Priority to BRPI0917953-4A priority patent/BRPI0917953B1/pt
Priority to EP09804758.2A priority patent/EP2320416B1/de
Publication of WO2010016271A1 publication Critical patent/WO2010016271A1/ja

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    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/002—Dynamic bit allocation
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/02—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using spectral analysis, e.g. transform vocoders or subband vocoders
    • G10L19/0204—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using spectral analysis, e.g. transform vocoders or subband vocoders using subband decomposition
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/04—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using predictive techniques
    • G10L19/16—Vocoder architecture
    • G10L19/18—Vocoders using multiple modes
    • G10L19/24—Variable rate codecs, e.g. for generating different qualities using a scalable representation such as hierarchical encoding or layered encoding
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00—Speech or voice signal processing techniques to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/02—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using spectral analysis, e.g. transform vocoders or subband vocoders
    • G10L19/0212—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using spectral analysis, e.g. transform vocoders or subband vocoders using orthogonal transformation
    • G—PHYSICS
    • G10—MUSICAL INSTRUMENTS; ACOUSTICS
    • G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis
    • G10L19/02—Speech or audio signals analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signals, using source filter models or psychoacoustic analysis using spectral analysis, e.g. transform vocoders or subband vocoders
    • G10L19/032—Quantisation or dequantisation of spectral components

Definitions

  • the present invention relates to a spectrum smoothing device, a coding device, a decoding device, a communication terminal device, a base station device, and a spectrum smoothing method for smoothing the spectrum of an audio signal.
  • the audio signal is orthogonally transformed (time-frequency conversion), the frequency component (spectrum) of the audio signal is calculated, and the calculated spectrum is subjected to processing such as linear conversion and nonlinear conversion.
  • processing such as linear conversion and nonlinear conversion.
  • Various techniques for improving the quality of a decoded signal have been developed (see, for example, Patent Document 1).
  • a frequency spectrum included in a speech signal is analyzed from a speech signal having a fixed time length, and a nonlinear conversion process that emphasizes the higher the spectrum intensity value of the analyzed spectrum is. I do.
  • linear smoothing processing is performed in the frequency domain on the spectrum subjected to nonlinear transformation processing.
  • Patent Document 1 has a problem that the amount of processing computation becomes enormous because nonlinear conversion processing is performed on all samples of a spectrum obtained from a speech signal.
  • simply extracting a part of the sample from the spectrum sample and performing the nonlinear conversion process on the extracted sample may result in smoothing the spectrum after nonlinear conversion.
  • An object of the present invention is a spectrum that can significantly reduce the amount of processing operations while maintaining good speech quality in a configuration in which smoothing is performed after nonlinear conversion is performed on a spectrum calculated from an audio signal.
  • a smoothing device, an encoding device, a decoding device, a communication terminal device, a base station device, and a spectrum smoothing method are provided.
  • the spectrum smoothing apparatus of the present invention includes a time-frequency converting means for generating a frequency component by time-frequency converting an input signal, a subband dividing means for dividing the frequency component into a plurality of subbands, For each divided subband, a representative value calculation means for calculating a representative value of the subband using a calculation of an arithmetic average and a multiplication operation using the calculation result, and a representative value for each subband A non-linear conversion means for performing non-linear conversion and a smoothing means for smoothing the representative value subjected to the non-linear conversion in the frequency domain are adopted.
  • the spectrum smoothing method of the present invention includes a time-frequency conversion step for generating a frequency component by time-frequency conversion of an input signal, a subband division step for dividing the frequency component into a plurality of subbands, For each divided subband, a representative value calculating step of calculating a representative value of the subband using an arithmetic average calculation and a multiplication operation using the calculation result, and a representative value for each subband
  • a non-linear conversion step for performing non-linear conversion and a smoothing step for smoothing the representative value subjected to the non-linear conversion in a frequency domain are provided.
  • FIG. 3 is a block diagram showing a main configuration of the spectrum smoothing apparatus according to Embodiment 1.
  • FIG. 3 is a block diagram showing a main configuration of a representative value calculation unit according to the first embodiment. Schematic diagram showing the configuration of subbands and subgroups of an input signal in the first embodiment
  • FIG. 3 is a block diagram showing a configuration of a communication system having an encoding device and a decoding device according to Embodiment 2 of the present invention.
  • FIG. 5 is a block diagram showing a main configuration inside the encoding apparatus shown in FIG. 5 according to the second embodiment. The block diagram which shows the main structures inside the 2nd layer encoding part shown in FIG.
  • FIG. 7 is a flowchart showing a processing procedure for searching for the optimum pitch coefficient T p ′ for the subband SB p in the search unit shown in FIG. 7 according to the second embodiment.
  • FIG. 5 is a block diagram showing a main configuration inside the decoding apparatus shown in FIG. 5 according to the second embodiment.
  • FIG. 1 is a spectrum diagram for explaining the outline of the spectrum smoothing method according to the present embodiment.
  • Fig. 1A shows the spectrum of the input signal.
  • the spectrum of the input signal is divided into a plurality of subbands.
  • FIG. 1B shows the state of the spectrum of the input signal divided into a plurality of subbands.
  • the spectrum diagram of FIG. 1 is for explaining the outline of the present invention.
  • the present invention is not limited to the number of subbands in the figure.
  • a representative value is calculated for each subband. Specifically, the samples in the subband are further divided into a plurality of subgroups. Then, the arithmetic average (arithmetic mean) of the absolute value of the spectrum is calculated for each subgroup.
  • the geometric mean (geometric mean) of the arithmetic mean values of each subgroup is calculated for each subband. Note that the geometric mean value is not yet an accurate geometric mean value at this time, but a value obtained by simply multiplying the arithmetic mean values of each subgroup is calculated. Sought after. The above processing is for further reduction of the calculation amount, and of course, an accurate geometric average value may be obtained at this point.
  • FIG. 1C shows the representative value of each subband superimposed on the spectrum of the input signal indicated by the dotted line.
  • FIG. 1C shows an accurate geometric average value as a representative value instead of a value obtained by simply multiplying the arithmetic average value of each subgroup.
  • a non-linear transformation for example, logarithmic transformation
  • smoothing processing is performed in the frequency domain.
  • inverse nonlinear transformation for example, logarithmic inverse transformation
  • a smoothed spectrum is calculated for each subband.
  • FIG. 1D shows a smoothed spectrum for each subband superimposed on the spectrum of the input signal indicated by the dotted line.
  • the spectrum smoothing apparatus smoothes an input spectrum and outputs a smoothed spectrum (hereinafter referred to as “smoothed spectrum”) as an output signal. More specifically, the spectrum smoothing apparatus divides the input signal into N samples (N is a natural number), and performs smoothing processing for each frame with N samples as one frame.
  • xn represents the (n + 1) th sample among the input signals divided by N samples.
  • FIG. 2 shows a main configuration of spectrum smoothing apparatus 100 according to the present embodiment.
  • the spectrum smoothing apparatus 100 shown in FIG. 2 mainly includes a time-frequency conversion processing unit 101, a subband division unit 102, a representative value calculation unit 103, a nonlinear conversion unit 104, a smoothing unit 105, and an inverse nonlinear conversion unit 106. Composed.
  • the time-frequency conversion processing unit 101 performs Fast Fourier Transform (FFT) on the input signal xn , and calculates a spectrum S1 (k) (hereinafter, input spectrum) of the frequency component.
  • FFT Fast Fourier Transform
  • the time-frequency conversion processing unit 101 outputs the input spectrum S1 (k) to the subband dividing unit 102.
  • the subband division unit 102 divides the input spectrum S1 (k) input from the time-frequency conversion processing unit 101 into P subbands (P is an integer of 2 or more).
  • P is an integer of 2 or more.
  • Subband splitting section 102 outputs a spectrum divided into subbands (hereinafter also referred to as “subband spectrum”) to representative value calculation section 103.
  • the representative value calculation unit 103 calculates a representative value for each subband of the input spectrum divided into subbands input from the subband division unit 102, and the calculated representative value for each subband is a nonlinear conversion unit. To 104. Detailed processing of the representative value calculation unit 103 will be described later.
  • FIG. 3 shows an internal configuration of the representative value calculation unit 103.
  • the representative value calculation unit 103 illustrated in FIG. 3 includes an arithmetic average calculation unit 201 and a geometric average calculation unit 202.
  • the subband spectrum is input from the subband dividing unit 102 to the arithmetic mean calculating unit 201.
  • the arithmetic mean calculation unit 201 further divides each subband of the input subband spectrum into Q subgroups (0th subgroup to Q-1 subgroup) (Q is an integer of 2 or more). .
  • Q is an integer of 2 or more.
  • each of the Q subgroups is composed of R samples (R is an integer of 2 or more).
  • R is an integer of 2 or more.
  • each of the Q subgroups is composed of R samples, but the number of samples in each subgroup may of course be different.
  • FIG. 4 shows a configuration example of subbands and subgroups.
  • FIG. 4 shows an example in which the number of samples constituting one subband is 8, the number of subgroups Q constituting the subband is 2, and the number of samples R in the subgroup is 4.
  • the arithmetic mean calculation unit 201 uses, for each of the Q subgroups, an arithmetic average (arithmetic mean) of the absolute values of the spectra (FFT coefficients) included in each subgroup using Equation (1). ) Is calculated.
  • AVE1 q is a spectrum included in the q-th sub-group arithmetic mean of the absolute value of the (FFT coefficients) (arithmetic mean)
  • BS q is the leading sample of the q subgroup Indicates the index.
  • P is the number of subbands.
  • the larger the value is, the more nonlinear the characteristic is enhanced, and the first subband logarithmic representative value spectrum AVE3 p (p 0 to P ⁇ 1) is calculated.
  • logarithmic transformation is performed as the nonlinear transformation processing will be described.
  • the subband arithmetic average value spectrum AVE1 p of each subband is simply multiplied, but the processing of the equation (4) in the nonlinear conversion unit 104 is performed.
  • the geometric mean (geometric mean) is calculated.
  • the reciprocal number of the subgroup number Q is multiplied using Formula (4).
  • Equation (5) shows the smoothing filtering processing
  • MA_LEN indicates the degree of smoothing filtering
  • W i represents the weight of a smoothing filter.
  • Equation (5) is a logarithmic smoothing spectrum calculation when the subband index p is p ⁇ (MA_LEN-1) / 2 and p ⁇ P-1- (MA_LEN-1) / 2. Is the method. When the subband index p is near the head or near the tail, the spectrum is smoothed using Equation (6) and Equation (7) in consideration of boundary conditions.
  • the smoothing unit 105 may perform smoothing by a simple moving average as the smoothing processing by the smoothing filtering process as described above (when Wi is 1 for all i, the moving average). Smoothing).
  • a simple moving average as the smoothing processing by the smoothing filtering process as described above (when Wi is 1 for all i, the moving average). Smoothing).
  • the window function weight
  • a Hanning window or other window functions may be used.
  • the inverse non-linear transformation unit 106 outputs the smoothed spectrum values of all samples as the processing result of the spectrum smoothing apparatus 100.
  • the subband division unit 102 divides the input spectrum into a plurality of subbands, and the representative value calculation unit 103 performs arithmetic averaging, multiplication operation, or geometric for each subband.
  • the average value is used to calculate the representative value, and the non-linear conversion unit 104 performs non-linear conversion of characteristics that emphasize the larger the value for each representative value, and the smoothing unit 105 performs non-linear conversion for each subband.
  • the representative value is smoothed in the frequency domain.
  • the arithmetic average of the sample values in the subband is obtained by adopting a configuration in which the arithmetic value of the samples in the subband is combined with the multiplication operation or the geometric average to calculate the representative value of the subband.
  • the value (arithmetic mean value) that is, the average value in the linear region is simply set as the representative value of each subband, the voice quality may be deteriorated due to the variation in the size of the sample value in the subband. Can be avoided.
  • the fast Fourier transform is described as an example of the time-frequency conversion processing.
  • the present invention is not limited to this, and time-frequency conversion other than the fast Fourier transform (FFT) is described.
  • frequency components spectrums
  • FFT fast Fourier transform
  • FIG. 2 auditory masking value
  • the nonlinear conversion unit 104 converts the logarithmic domain using the equation (3) as a nonlinear conversion process, and then multiplies the reciprocal of the subgroup number Q using the equation (4). This is because the calculation amount can be further reduced because the calculation of the power root can be replaced with simple division (multiplication).
  • the present invention is not necessarily limited to the above-described configuration.
  • the smoothing unit 105 can obtain a representative value for each subband subjected to nonlinear transformation.
  • the calculation of Equation (4) may be omitted in the nonlinear conversion unit 104.
  • the representative value for each subband is first obtained as the arithmetic average value of the subgroups, and then the geometric average value of the arithmetic average values of all the subgroups in the subband.
  • the present invention is not limited to this, and when the number of samples constituting the subgroup is 1, that is, the arithmetic average value of each subgroup is not calculated, and the geometric average value of all the samples in the subband is calculated. The same can be applied to the case of using a representative value of.
  • the geometric mean value may not be accurately calculated, and the geometric mean value may be calculated in the logarithmic region by multiplying the reciprocal of the number of subgroups after performing non-linear transformation.
  • the spectrum values of the samples in the same subband are all set to the same value.
  • the present invention is not limited to this, and an inverse smoothing processing unit is provided after the inverse nonlinear transformation unit 106, and the inverse smoothing processing unit weights each sample within each subband and performs inverse smoothing. Processing may be performed. Further, this inverse smoothing process may not be a completely opposite conversion to the smoothing unit 105.
  • the nonlinear conversion unit 104 performs logarithmic conversion as the nonlinear conversion process and the inverse nonlinear conversion unit 106 performs logarithmic inverse conversion as the inverse nonlinear conversion process.
  • the present invention is not limited to this, and a power or the like may be used, and the inverse processing of the nonlinear transformation processing may be performed in the inverse nonlinear transformation processing.
  • the calculation of the power root can be replaced with a simple division (multiplication), so that the amount of calculation can be further reduced. This is because the nonlinear transformation unit 104 performs logarithmic transformation as nonlinear transformation.
  • the number of subbands and subgroups for example, when the sampling frequency of the input signal is 32 kHz and the length of one frame is 20 msec, that is, when there are 640 samples of the input signal, the number of subbands is set to 80. As an example, the number of subgroups is set to 2, the number of samples of each subgroup is set to 4, and the order of smoothing filtering is set to 7. However, the present invention is not limited to the setting, and can be similarly applied when these are set to other numerical values.
  • the spectrum smoothing apparatus and spectrum smoothing method according to the present invention include a speech coding apparatus and speech coding method, a speech decoding apparatus and speech decoding method, a speech recognition apparatus and speech recognition method, and the like. It can be applied to all of the spectral smoothing parts to be performed.
  • a spectrum envelope is calculated from LPC (Linear Predictive Coefficient) as a preprocessing for a lowband spectrum performed to calculate a parameter for generating a highband spectrum.
  • LPC Linear Predictive Coefficient
  • the spectrum smoothing method according to the present invention is replaced with the spectrum smoothing method according to the present invention instead of the spectrum envelope used in the spectrum envelope removal process of Patent Document 2. It is also possible to use a smoothed spectrum calculated by applying to the spectrum.
  • the configuration in which the input spectrum S1 (k) to be input is divided into P subbands (P is an integer of 2 or more) having the same number of samples in each subband has been described.
  • the present invention is not limited to this, and the present invention can be similarly applied to configurations in which the number of samples in each subband is different.
  • a configuration in which the subband is divided so that the number of samples is smaller as the subband on the low frequency side and the number of samples is larger as the subband on the high frequency side is given.
  • the human auditory sensation has a lower frequency resolution at the higher frequency side, and thus the spectrum can be smoothed more efficiently by adopting the above configuration.
  • each of the Q subgroups is composed of R samples, but the present invention is not limited to this, and the number of samples is smaller in the lower frequency subgroup,
  • the present invention can be similarly applied to a configuration in which a subgroup is divided so that the number of samples in the higher frequency subgroup increases.
  • the weighted moving average is described as an example of the smoothing process.
  • the present invention is not limited to this, and can be similarly applied to various smoothing processes.
  • the number of taps of the moving average filter is not symmetrical and the number of taps in the high range is small. It doesn't matter.
  • smoothing processing more suitable for audibility can be performed by using a moving average filter having a small number of taps on the high frequency side.
  • the present invention can be similarly applied to the case of using a left-right asymmetric moving average filter that has a larger number of taps in a higher frequency range.
  • FIG. 5 is a block diagram showing a configuration of a communication system having an encoding device and a decoding device according to Embodiment 2 of the present invention.
  • the communication system includes an encoding device and a decoding device, and can communicate with each other via a transmission path. Note that both the encoding device and the decoding device are usually mounted and used in a base station device or a communication terminal device.
  • the encoding device 301 divides the input signal into N samples (N is a natural number), and encodes each frame with N samples as one frame.
  • n indicates the (n + 1) th signal element in the input signal divided by N samples.
  • the encoded input information (encoded information) is transmitted to the decoding device 303 via the transmission path 302.
  • the decoding device 303 receives the encoded information transmitted from the encoding device 301 via the transmission path 302 and decodes it to obtain an output signal.
  • FIG. 6 is a block diagram showing the main components inside coding apparatus 301 shown in FIG.
  • the downsampling processing unit 311 downsamples the sampling frequency of the input signal from SR input to SR base (SR base ⁇ SR input ), and after downsampling the downsampled input signal
  • the input signal is output to first layer encoding section 312.
  • the first layer coding unit 312 performs coding on the downsampled input signal input from the downsampling processing unit 311 using, for example, a CELP (Code (Excited Linear Prediction) method speech coding method.
  • CELP Code (Excited Linear Prediction) method speech coding method.
  • One-layer encoded information is generated, and the generated first layer encoded information is output to first layer decoding section 313 and encoded information integration section 317.
  • the first layer decoding unit 313 decodes the first layer encoded information input from the first layer encoding unit 312 using, for example, a CELP speech decoding method to generate a first layer decoded signal Then, the generated first layer decoded signal is output to the upsampling processing unit 314.
  • the upsampling processing unit 314 upsamples the sampling frequency of the first layer decoded signal input from the first layer decoding unit 313 from SR base to SR input, and first upsamples the upsampled first layer decoded signal. It outputs to the time-frequency conversion process part 315 as a layer decoding signal.
  • the delay unit 318 gives a delay of a predetermined length to the input signal. This delay is for correcting a time delay generated in the downsampling processing unit 311, the first layer encoding unit 312, the first layer decoding unit 313, and the upsampling processing unit 314.
  • the one-layer decoded signal yn is subjected to modified discrete cosine transform (MDCT).
  • MDCT modified discrete cosine transform
  • the time-frequency conversion processing unit 315 initializes the buffers buf1 n and buf2 n using “0” as an initial value according to the following equations (9) and (10).
  • the time - frequency conversion processing unit 315 MDCT according to the input signal x n, the following formula with respect to the first layer decoded signal y n after upsampling (11) and Equation (12), MDCT coefficients of the input signal (hereinafter , referred to as an input spectrum) S2 (k) and an up-sampled MDCT coefficients of the first layer decoded signal y n (hereinafter, referred to as a first layer decoded spectrum) Request S1 (k).
  • k represents the index of each sample in one frame.
  • the time-frequency conversion processing unit 315 obtains x n ′, which is a vector obtained by combining the input signal x n and the buffer buf1 n by the following equation (13). Further, the time-frequency conversion processing unit 315 obtains y n ′, which is a vector obtained by combining the up-sampled first layer decoded signal y n and the buffer buf2 n by the following equation (14).
  • the time-frequency conversion processing unit 315 updates the buffers buf1 n and buf2 n according to equations (15) and (16).
  • the time-frequency conversion processing unit 315 outputs the input spectrum S2 (k) and the first layer decoded spectrum S1 (k) to the second layer encoding unit 316.
  • Second layer encoding section 316 generates second layer encoded information using input spectrum S2 (k) and first layer decoded spectrum S1 (k) input from time-frequency conversion processing section 315, and generates The encoded second layer encoded information is output to encoded information integration section 317. Details of second layer encoding section 316 will be described later.
  • the encoded information integration unit 317 integrates and integrates the first layer encoded information input from the first layer encoding unit 312 and the second layer encoded information input from the second layer encoding unit 316. If necessary, a transmission error code or the like is added to the information source code, which is output to the transmission line 302 as encoded information.
  • Second layer encoding section 316 includes band dividing section 360, spectrum smoothing section 361, filter state setting section 362, filtering section 363, search section 364, pitch coefficient setting section 365, gain encoding section 366, and multiplexing section 367. Each part performs the following operations.
  • a portion corresponding to the subband SB p in the input spectrum S2 (k) is referred to as a subband spectrum S2 p (k) (BS p ⁇ k ⁇ BS p + BW p ).
  • the spectrum smoothing unit 361 performs the smoothing process on the first layer decoded spectrum S1 (k) (0 ⁇ k ⁇ FL) input from the time-frequency conversion processing unit 315, and performs the smoothing after the smoothing process
  • First layer decoded spectrum S 1 ′ (k) (0 ⁇ k ⁇ FL) is output to filter state setting section 362.
  • FIG. 8 shows the internal configuration of the spectrum smoothing unit 361.
  • the spectrum smoothing unit 361 mainly includes a subband division unit 102, a representative value calculation unit 103, a nonlinear transformation unit 104, a smoothing unit 105, and an inverse nonlinear transformation unit 106.
  • each processing unit is the same as the processing unit described in the first embodiment, the same reference numerals are given and description thereof is omitted.
  • the filter state setting unit 362 sets the smoothed first layer decoded spectrum S1 ′ (k) (0 ⁇ k ⁇ FL) input from the spectrum smoothing unit 361 as the internal state of the filter used in the subsequent filtering unit 363. To do.
  • the smoothed first layer decoded spectrum S1 '(k) is stored as an internal state (filter state) of the filter in the band of 0 ⁇ k ⁇ FL of the spectrum S (k) of all frequency bands in the filtering unit 363.
  • the filtering unit 363 outputs the estimated spectrum S2 p ′ (k) of the subband SB p to the search unit 364. Details of the filtering process in the filtering unit 363 will be described later. It is assumed that the number of taps of a multi-tap can take an arbitrary value (integer) of 1 or more.
  • the search unit 364 receives the estimated spectrum S2 p ′ (k) of the subband SB p input from the filtering unit 363 and the time-frequency conversion processing unit 315 based on the band division information input from the band dividing unit 360.
  • the similarity with each subband spectrum S2 p (k) in the high frequency part (FL ⁇ k ⁇ FH) of the input spectrum S2 (k) is calculated.
  • the similarity is calculated by, for example, correlation calculation.
  • the processes of the filtering unit 363, the search unit 364, and the pitch coefficient setting unit 365 constitute a closed loop search process for each subband, and in each closed loop, the search unit 364 is changed from the pitch coefficient setting unit 365 to the filtering unit 363.
  • the degree of similarity corresponding to each pitch coefficient is calculated by variously changing the input pitch coefficient T.
  • the search unit 364 obtains an optimum pitch coefficient T p ′ (however, in the range of Tmin to Tmax) that maximizes the similarity in the closed loop corresponding to the subband SB p , and P optimal
  • the pitch coefficient is output to multiplexing section 367.
  • Search unit 364 uses each optimum pitch coefficient T p ′ to calculate a partial band of the first layer decoded spectrum that is similar to each subband SB p .
  • the pitch coefficient setting unit 365 When the pitch coefficient setting unit 365 performs a closed loop search process corresponding to the first subband SB 0 together with the filtering unit 363 and the search unit 364 under the control of the search unit 364, the pitch coefficient T is determined in advance. The output is sequentially output to the filtering unit 363 while changing little by little within the obtained search range Tmin to Tmax.
  • the gain encoding unit 366 calculates gain information for the high frequency part (FL ⁇ k ⁇ FH) of the input spectrum S2 (k) input from the time-frequency conversion processing unit 315. Specifically, gain encoding section 366 divides frequency band FL ⁇ k ⁇ FH into J subbands, and obtains the spectrum power for each subband of input spectrum S2 (k). In this case, the spectrum power B j of the (j + 1) -th subband is expressed by the following equation (17).
  • BL j represents the minimum frequency of the (j + 1) th subband
  • BH j represents the maximum frequency of the (j + 1) th subband.
  • the estimated spectrum S2 ′ (k) of the high frequency region is constructed.
  • gain encoding section 366 similarly to the case of calculating the spectral power for the input spectrum S2 (k), j to the following formula 'spectrum power B of each subband (k)' estimated spectrum S2 ( Calculate according to 18).
  • the gain encoding unit 366 performs the spectrum power fluctuation amount V j for each subband of the estimated spectrum S2 ′ (k) with respect to the input spectrum S2 (k). Is calculated according to equation (19).
  • the gain encoding unit 366 encodes the variation amount V j and outputs an index corresponding to the encoded variation amount VQ j to the multiplexing unit 367.
  • the filtering unit 363 uses the filter state input from the filter state setting unit 362, the pitch coefficient T input from the pitch coefficient setting unit 365, and the band division information input from the band division unit 360, and uses the subband.
  • the transfer function F (z) of the filter used in the filtering unit 363 is expressed by the following equation (20).
  • T represents a pitch coefficient given from the pitch coefficient setting unit 365
  • ⁇ i represents a filter coefficient stored in advance.
  • values such as ( ⁇ ⁇ 1 , ⁇ 0 , ⁇ 1 ) (0.2, 0.6, 0.2), (0.3, 0.4, 0.3) are also appropriate.
  • M 1.
  • M is an index related to the number of taps.
  • the smoothed first layer decoded spectrum S1 '(k) is stored as an internal state (filter state) of the filter in the band of 0 ⁇ k ⁇ FL of the spectrum S (k) of all frequency bands.
  • the estimated spectrum S2 p ′ (k) of the subband SB p is stored by the filtering process of the following procedure. That is, a spectrum S (k ⁇ T) having a frequency lower than this k by T is basically substituted into S2 p ′ (k). However, in order to increase the smoothness of the spectrum, actually, a spectrum ⁇ i .multidot. ⁇ Obtained by multiplying a spectrum S (k ⁇ T + i) in the vicinity away from the spectrum S (k ⁇ T) by a predetermined filter coefficient ⁇ i. A spectrum obtained by adding S (k ⁇ T + i) for all i is substituted into S2 p ′ (k). This process is expressed by the following equation (21).
  • the above filtering process is performed by clearing S (k) to zero each time in the range of BS p ⁇ k ⁇ BS p + BW p every time the pitch coefficient T is given from the pitch coefficient setting unit 365. That is, every time the pitch coefficient T changes, S (k) is calculated and output to the search unit 364.
  • search section 364 initializes minimum similarity D min , which is a variable for storing the minimum value of similarity, to “+ ⁇ ” (ST110).
  • search unit 364 according to the following equation (22), similarity between the high frequency part (FL ⁇ k ⁇ FH) of the input spectrum S2 (k) at a certain pitch coefficient and the estimated spectrum S2 p ′ (k) D is calculated (ST120).
  • M ′ represents the number of samples when the similarity D is calculated, and may be an arbitrary value equal to or smaller than the bandwidth of each subband. It should be noted that S2 p ′ (k) does not exist in the equation (22) because this represents S2 p ′ (k) using BS p and S2 ′ (k).
  • search section 364 determines whether calculated similarity D is smaller than minimum similarity D min (ST130). When the similarity D calculated in ST120 is smaller than the minimum similarity Dmin (ST130: “YES”), search section 364 substitutes similarity D into minimum similarity Dmin (ST140). On the other hand, when the similarity D calculated in ST120 is greater than or equal to the minimum similarity D min (ST130: “NO”), search section 364 determines whether or not the process over the search range has ended. That is, search section 364 determines whether or not the similarity is calculated according to the above equation (22) in ST120 for each of all pitch coefficients in the search range (ST150).
  • search section 364 If the process has not been completed over the search range (ST150: “NO”), search section 364 returns the process to ST120 again. Then, search section 364 calculates similarity according to equation (22) for a pitch coefficient different from the case where similarity was calculated according to equation (22) in the previous ST120 procedure. On the other hand, when the process over the search range is completed (ST150: “YES”), the search unit 364 sets the pitch coefficient T corresponding to the minimum similarity D min to the multiplexing unit 367 as the optimum pitch coefficient T p ′. Output (ST160).
  • FIG. 11 is a block diagram illustrating a main configuration inside the decoding device 303.
  • the encoded information separation unit 331 separates the first layer encoded information and the second layer encoded information from the input encoded information, and the first layer encoded information is first layer decoded. And outputs the second layer encoded information to second layer decoding section 335.
  • the first layer decoding unit 332 performs decoding on the first layer encoded information input from the encoded information separation unit 331, and outputs the generated first layer decoded signal to the upsampling processing unit 333.
  • the operation of first layer decoding section 332 is the same as that of first layer decoding section 313 shown in FIG.
  • the upsampling processing unit 333 performs a process of upsampling the sampling frequency from the SR base to the SR input on the first layer decoded signal input from the first layer decoding unit 332, and obtains the first layer decoding after the upsampling obtained.
  • the signal is output to the time-frequency conversion processing unit 334.
  • the time-frequency conversion processing unit 334 performs orthogonal transform processing (MDCT) on the first layer decoded signal after upsampling input from the upsampling processing unit 333, and the MDCT of the first layer decoded signal after upsampling obtained.
  • the coefficient (hereinafter referred to as first layer decoded spectrum) S1 (k) is output to second layer decoding section 335.
  • the operation of the time-frequency conversion processing unit 334 is the same as the processing for the first layer decoded signal after upsampling of the time-frequency conversion processing unit 315 shown in FIG.
  • Second layer decoding section 335 uses first layer decoded spectrum S1 (k) input from time-frequency conversion processing section 334 and second layer encoded information input from encoded information separating section 331 to A second layer decoded signal including a band component is generated and output as an output signal.
  • FIG. 12 is a block diagram showing the main configuration inside second layer decoding section 335 shown in FIG.
  • the spectrum smoothing unit 352 performs a smoothing process on the first layer decoded spectrum S1 (k) (0 ⁇ k ⁇ FL) input from the time-frequency conversion processing unit 334, and performs smoothing after the smoothing.
  • One-layer decoded spectrum S1 ′ (k) (0 ⁇ k ⁇ FL) is output to filter state setting section 353. Since the process of the spectrum smoothing unit 352 is the same as that of the spectrum smoothing unit 361 in the second layer encoding unit 316, the description thereof is omitted here.
  • the filter state setting unit 353 sets the smoothed first layer decoded spectrum S1 ′ (k) (0 ⁇ k ⁇ FL) input from the spectrum smoothing unit 352 as the filter state used by the filtering unit 354.
  • S (k) when the spectrum of all frequency bands 0 ⁇ k ⁇ FH in the filtering unit 354 is referred to as S (k) for convenience, the smoothed first layer decoded spectrum is included in the band of 0 ⁇ k ⁇ FL of S (k).
  • S1 ′ (k) is stored as the internal state (filter state) of the filter.
  • the configuration and operation of the filter state setting unit 353 are the same as those of the filter state setting unit 362 shown in FIG.
  • the filtering unit 354 includes a multi-tap pitch filter (the number of taps is greater than 1).
  • the filter function shown in the above equation (20) is used. However, in this case, the filtering process and the filter function are obtained by replacing T in Equation (20) and Equation (21) with T p ′.
  • the gain decoding unit 355 decodes the index of the encoded variation amount VQ j input from the separation unit 351, and obtains a variation amount VQ j that is a quantized value of the variation amount V j .
  • the spectrum adjustment unit 356 adjusts the spectrum shape in the frequency band FL ⁇ k ⁇ FH of the estimated spectrum S2 ′ (k), generates the decoded spectrum S3 (k), and outputs it to the time-frequency conversion processing unit 357. To do.
  • spectrum adjustment section 356 converts first layer decoded spectrum S1 (k) (0 ⁇ k ⁇ FL) input from time-frequency conversion processing section 334 into decoded spectrum S3 ( Substitute in the low-frequency part (0 ⁇ k ⁇ FL) of k).
  • the low frequency part (0 ⁇ k ⁇ FL) of the decoded spectrum S3 (k) is composed of the first layer decoded spectrum S1 (k), and the high frequency part (FL ⁇ k ⁇ FH) of the decoded spectrum S3 (k).
  • the time-frequency conversion processing unit 357 orthogonally transforms the decoded spectrum S3 (k) input from the spectrum adjustment unit 356 into a time domain signal, and outputs the obtained second layer decoded signal as an output signal.
  • processing such as appropriate windowing and overlay addition is performed as necessary to avoid discontinuities between frames.
  • the time-frequency conversion processing unit 357 has a buffer buf ′ (k) therein, and initializes the buffer buf ′ (k) as shown in the following equation (25).
  • time-frequency conversion processing unit 357 obtains the second layer decoded signal y n ′′ according to the following equation (26) using the second layer decoded spectrum S3 (k) input from the spectrum adjusting unit 356. Output.
  • Z4 (k) is a vector obtained by combining the decoded spectrum S3 (k) and the buffer buf ′ (k) as shown in Expression (27) below.
  • the time-frequency conversion processing unit 357 updates the buffer buf ′ (k) according to the following equation (28).
  • the time-frequency conversion processing unit 357 outputs the decoded signal y n ′′ as an output signal.
  • a pre-processing is performed on the low-frequency spectrum.
  • a smoothing process combining the arithmetic mean and the geometric mean is performed.
  • the present invention at the time of band extension encoding, smoothing processing is performed on the low-frequency decoded spectrum obtained by decoding, the high-frequency spectrum is estimated using the smoothed low-frequency decoded spectrum,
  • the configuration for encoding has been described, the present invention is not limited to this, and the configuration is such that the low-frequency spectrum of the input signal is smoothed, the high-frequency spectrum is estimated from the smoothed input spectrum, and the encoding is performed. The same applies to.
  • the spectrum smoothing apparatus and the spectrum smoothing method according to the present invention are not limited to the above-described embodiment, and can be implemented with various modifications.
  • each embodiment can be implemented in combination as appropriate.
  • the present invention can also be applied to a case where a signal processing program is recorded and written on a machine-readable recording medium such as a memory, a disk, a tape, a CD, or a DVD, and the operation is performed. Actions and effects similar to those of the form can be obtained.
  • each functional block used in the description of the above embodiment is typically realized as an LSI which is an integrated circuit. These may be individually made into one chip, or may be made into one chip so as to include a part or all of them.
  • the name used here is LSI, but it may also be called IC, system LSI, super LSI, or ultra LSI depending on the degree of integration.
  • the method of circuit integration is not limited to LSI, and implementation with a dedicated circuit or a general-purpose processor is also possible.
  • An FPGA Field Programmable Gate Array
  • a reconfigurable / processor that can reconfigure the connection and setting of circuit cells inside the LSI may be used.
  • the spectrum smoothing device, the coding device, the decoding device, the communication terminal device, the base station device, and the spectrum smoothing method according to the present invention can realize smoothing in the spectrum domain with a small amount of calculation, for example, a packet It can be applied to a communication system, a mobile communication system, and the like.

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PCT/JP2009/003799 2008-08-08 2009-08-07 スペクトル平滑化装置、符号化装置、復号装置、通信端末装置、基地局装置及びスペクトル平滑化方法 WO2010016271A1 (ja)

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US13/057,454 US8731909B2 (en) 2008-08-08 2009-08-07 Spectral smoothing device, encoding device, decoding device, communication terminal device, base station device, and spectral smoothing method
JP2010523772A JP5419876B2 (ja) 2008-08-08 2009-08-07 スペクトル平滑化装置、符号化装置、復号装置、通信端末装置、基地局装置及びスペクトル平滑化方法
RU2011104350/08A RU2510536C9 (ru) 2008-08-08 2009-08-07 Устройство сглаживания спектра, устройство кодирования, устройство декодирования, устройство терминала связи, устройство базовой станции и способ сглаживания спектра
DK09804758.2T DK2320416T3 (da) 2008-08-08 2009-08-07 Indretning til spektral udglatning, kodningsindretning, afkodningsindretning, kommunikationsterminalindretning, basisstationsindretning og fremgangsmåde til spektral udglatning
CN2009801283823A CN102099855B (zh) 2008-08-08 2009-08-07 频谱平滑化装置、编码装置、解码装置、通信终端装置、基站装置以及频谱平滑化方法
MX2011001253A MX2011001253A (es) 2008-08-08 2009-08-07 Dispositivo de filtrado espectral, dispositivo de codificacion, dispositivo de decodificacion, dispositivo de terminal de comunicacion, dispositivo de estacion base y metodo de filtrado espectral.
ES09804758.2T ES2452300T3 (es) 2008-08-08 2009-08-07 Dispositivo de alisamiento espectral, dispositivo de codificación, dispositivo de decodificación, dispositivo de terminal de comunicación, dispositivo de estación base y método de alisamiento espectral
BRPI0917953-4A BRPI0917953B1 (pt) 2008-08-08 2009-08-07 Aparelho de atenuação de espectro, aparelho de codificação, aparelho terminal de comunicação, aparelho de estação base e método de atenuação de espectro.
EP09804758.2A EP2320416B1 (de) 2008-08-08 2009-08-07 Spektralglättungsvorrichtung, Kodierungsvorrichtung, Dekodierungsvorrichtung, Kommunikationsendgerät, Basisstationsvorrichtung und Spektralglättungsverfahren

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CN102099855B (zh) 2012-09-26
KR20110049789A (ko) 2011-05-12
JPWO2010016271A1 (ja) 2012-01-19
US20110137643A1 (en) 2011-06-09
CN102099855A (zh) 2011-06-15

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